Multipronged Modeling of Subcellular Self-Organization

亚细胞自组织的多管齐下建模

• 批准号: 1953430
• 负责人: Alexander Mogilner
• 金额: $ 35.03万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1953430&HistoricalAwards=false
• 关键词: Multipronged; Modeling; Subcellular; Self; Organization

Cells in our body have a certain structure: nucleus and other organelles are not placed at random, but rather positioned in certain locations to optimize transport and communication inside the cell. These organelles’ positions are not pre-programmed; the organelles find their positions through a process of mechanical self-organization. Specifically, the organelles extend dynamic ‘arms’ made of cytoskeletal proteins, and use these arms to grab, push and pull each other. The ensuing tug-of-war leads to a complex mechanical equilibrium that determines organelles’ positions. These positions can be measured in microscopic images, while underlying mechanical forces are impossible to measure. This project will solve an inverse problem by reverse-engineering the forces from the positions of organelles inside the cell. This project will also address this problem from multiple directions: considering organelles to be tiny rigid particles interacting by long-range forces, considering an abstract viscous fluid made of organelles, and finally mimicking dynamics and mechanics of all essential molecules and organelles in a computer simulation. The project will use these simulations to screen hundreds of thousands of possible forces, and experimental data to distill the correct forces in the cell. The mathematical models will be developed, tested and refined for two fundamental cellular systems: mitotic spindle (molecular machine segregating chromosomes in cell division) and multiple nuclei in large muscle cells. The models will help experimentalists to understand which molecules are responsible for proper architecture of healthy cells and for defects in aging muscles and dividing cancer cells. In the process, interdisciplinary researchers will be trained, novel courses on modeling biosystems will be developed, and K-12 students will be introduced to quantitative biology.One of the fundamental challenges of cell biology is to define principles of spatial organization of the cell. Organelle positioning is essentially a mechanical phenomenon: a set of intracellular forces is responsible for placing the organelles. These forces are generated by activities of cytoskeleton, a dynamic scaffold of elastic fibers and molecular motor proteins immersed into viscous cytosol, more specifically, the microtubule-kinesin-dynein force-generating system. The main goal is to use experimental data to reverse-engineer the intracellular forces and understand underlying molecular mechanisms. To achieve this goal, novel methods to generate multiple models and automatically screen the models against the experimental data will be developed and applied to two phenomena: self-organization of a bipolar mitotic spindle in multi-centrosomal cells, and dynamic nuclear positioning in multinucleated embryonic muscle cells. Specifically, a computer code will be developed that will generate a wide class of forces and screen the forces by detecting a small minority of the forces leading to the observed cell architectures. Multiple models (organelles as particles driven by pair-wise distance-dependent forces, energy-minimization models, continuous integro-differential and agent-based models) will be developed, compared and tested, machine learning will be used to accelerate the model screening. Collaboration with two experimental labs will result in discovery of molecular mechanisms of nuclei positioning in developing muscle cells and of dynamic architecture of mitotic spindle.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

我们体内的细胞具有一定的结构：细胞核和其他细胞器不是随机放置的，而是位于某些位置，以优化细胞内的运输和通信。这些细胞器的位置不是预先设定的;细胞器通过机械自组织过程找到它们的位置。具体来说，细胞器延伸由细胞骨架蛋白质组成的动态“手臂”，并使用这些手臂相互抓取，推拉。随后的拔河导致了一个复杂的机械平衡，决定了细胞器的位置。这些位置可以在显微图像中测量，而潜在的机械力是不可能测量的。这个项目将通过逆向工程从细胞内细胞器的位置来解决一个逆问题。该项目还将从多个方向解决这个问题：考虑细胞器是通过长程力相互作用的微小刚性粒子，考虑由细胞器组成的抽象粘性流体，最后在计算机模拟中模拟所有基本分子和细胞器的动力学和力学。该项目将使用这些模拟来筛选数十万种可能的力，并使用实验数据来提取细胞中的正确力。数学模型将开发，测试和完善两个基本的细胞系统：有丝分裂纺锤体（分子机器分离染色体在细胞分裂）和多个细胞核在大肌肉细胞。这些模型将帮助实验人员了解哪些分子负责健康细胞的正确结构以及衰老肌肉和分裂癌细胞的缺陷。在这个过程中，将培养跨学科的研究人员，将开发关于建模生物系统的新课程，并将向K-12学生介绍定量生物学。细胞生物学的基本挑战之一是定义细胞的空间组织原则。细胞器定位本质上是一种机械现象：一组细胞内力负责放置细胞器。这些力是由细胞骨架的活动产生的，细胞骨架是弹性纤维的动态支架，分子马达蛋白浸入粘性细胞质中，更具体地说，是微管-驱动蛋白-动力蛋白力产生系统。主要目标是利用实验数据来逆向工程细胞内的力量，并了解潜在的分子机制。为了实现这一目标，新的方法来生成多个模型和自动筛选的模型对实验数据将开发和应用到两个现象：自组织的双极有丝分裂纺锤体在多中心体细胞，和动态核定位在多核胚胎肌细胞。具体而言，将开发一种计算机代码，该代码将生成广泛的力类，并通过检测导致观察到的细胞架构的力中的一小部分来筛选力。将开发、比较和测试多个模型（细胞器作为由成对距离依赖力驱动的粒子、能量最小化模型、连续积分-微分模型和基于代理的模型），将使用机器学习来加速模型筛选。与两个实验室的合作将导致细胞核定位在发育中的肌肉细胞和有丝分裂纺锤体的动态结构的分子机制的发现。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

Protein friction and filament bending facilitate contraction of disordered actomyosin networks

蛋白质摩擦和丝弯曲促进无序肌动球蛋白网络的收缩

• DOI: 10.1016/j.bpj.2021.08.012
• 发表时间: 2021
• 期刊: Biophysical Journal
• 影响因子: 3.4
• 作者: Tam, Alexander K.Y.;Mogilner, Alex;Oelz, Dietmar B.
• 通讯作者: Oelz, Dietmar B.

Mechanical Torque Promotes Bipolarity of the Mitotic Spindle Through Multi-centrosomal Clustering

• DOI: 10.1007/s11538-021-00985-2
• 发表时间: 2022-02-01
• 期刊: BULLETIN OF MATHEMATICAL BIOLOGY
• 影响因子: 3.5
• 作者: Miles，Christopher E.;Zhu，Jie;Mogilner，Alex
• 通讯作者: Mogilner，Alex

Mechanics of Multicentrosomal Clustering in Bipolar Mitotic Spindles

• DOI: 10.1016/j.bpj.2020.06.004
• 发表时间: 2020-07-21
• 期刊: BIOPHYSICAL JOURNAL
• 影响因子: 3.4
• 作者: Chatterjee, Saptarshi;Sarkar, Apurba;Paul, Raja
• 通讯作者: Paul, Raja